Wanaku

Community AI and agents

Wanaku MCP router: an extensible routing engine for integrating enterprise systems with AI agents.

What can you do with Wanaku?

  • Agent Isolation — Agents call tools through Wanaku; they never reach backend systems directly
  • Policy Enforcement — LLM-powered evaluators + WASM action scripts classify, filter, and block tool calls in the proxy layer
  • Identity & Auth — Authentication and authorization via oauth2-proxy and Keycloak, enforced before actions reach backends
  • Tool Discovery — Auto-discover tools from upstream MCP servers; integration developers publish Camel routes as tools
  • Namespace Isolation — Organize tools and resources across isolated namespaces per team, tenant, or environment
  • Extensible Architecture — Plugin system via feature crates and a composable filter pipeline
  • Admin Dashboard — Web UI for managing tools, resources, prompts, and forwards
  • Container-Ready — Multi-arch images (x86_64, aarch64) published automatically

Install

The installation steps are in the documentation below. Documentation

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Wanaku — A Governed Action Proxy for AI Agents
  2. Key Features
  3. Quick Start
  4. Documentation
  5. Community
  6. Related Projects
  7. License

Wanaku — A Governed Action Proxy for AI Agents

Wanaku is a governed action proxy for AI agents. It sits between agents and the systems they act on, intercepting Model Context Protocol (MCP) tool calls, agent-to-agent messages, and inference traffic. Before version 0.2.0, the project was named Wanaku MCP Router. It was renamed to Wanaku Governed Execution Proxy to reflect its expanded scope.

Wanaku supports open standards for AI agents and provides first-class integration with enterprise frameworks, including Apache Camel and Quarkus. For example, integration developers build Apache Camel routes and use Wanaku's Camel Integration Capability to publish them as tools. Agents call those tools with parameters, but Wanaku runs the work. Agents never access backend systems directly. The proxy enforces policy, identity, data controls, and audit requirements.

The project name comes from the origin of guanaco, a camelid native to South America.

Key Features

  • Agent Isolation — Agents call tools through Wanaku; they never reach backend systems directly
  • Policy Enforcement — LLM-powered evaluators + WASM action scripts classify, filter, and block tool calls in the proxy layer
  • Identity & Auth — Authentication and authorization via oauth2-proxy and Keycloak, enforced before actions reach backends
  • Tool Discovery — Auto-discover tools from upstream MCP servers; integration developers publish Camel routes as tools
  • Namespace Isolation — Organize tools and resources across isolated namespaces per team, tenant, or environment
  • Extensible Architecture — Plugin system via feature crates and a composable filter pipeline
  • Admin Dashboard — Web UI for managing tools, resources, prompts, and forwards
  • Container-Ready — Multi-arch images (x86_64, aarch64) published automatically

Quick Start

Install

Download the latest early-access build on Linux or macOS:

curl -fsSL https://raw.githubusercontent.com/wanaku-ai/wanaku/main/get-wanaku.sh | bash

The installer detects the host platform, verifies the release checksum, and installs wanaku-server into $HOME/bin.

Override the destination with WANAKU_INSTALL_DIR.

Run wanaku-server and access http://localhost:8080 to enter the dashboard:

If you prefer a text interface, you may also download and use the Wanaku CLI from theWanaku Barn project.

Learn Wanaku

The easiest way to learn Wanaku is by following the guided tutorial.

The reference documentation, including the complete installation and configuration instructions, is available in the usage guide.

All tools from the remote server now appear in your local catalog. The client has no idea they're forwarded.

Documentation

The Wanaku Documentation website contains the full project documentation.

Contributors working on the project may want to refer to the development documentation:

Community

  • Wanaku Barn — Utilities for the Wanaku project: OpenShift/Kubernetes operator, CLI client, etc
  • Camel Integration Capability — Build Apache Camel routes and publish them as tools that agents can call through Wanaku

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

Frequently asked questions

What is Wanaku?

Wanaku MCP router: an extensible routing engine for integrating enterprise systems with AI agents.

How do I install Wanaku?

Follow the installation steps in its documentation, shown on this page and in its repository.

Is Wanaku open source?

Yes. Its code is on GitHub under the Apache-2.0 license.

Who maintains Wanaku?

It is published by wanaku-ai. AI.tn lists it but does not maintain or endorse it.

From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.